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Rag Agent Jobs (NOW HIRING)

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems. Must-Have Technical Skills * Strong hands-on experience in AI/ML development ...

Showing results 21-40

Rag Agent information

What are popular job titles related to Rag Agent jobs?

For Rag Agent jobs, the most frequently searched job titles are:

Applied AI Architect

Schiller Park, IL • On-site

Neshent Technologies
11 - 50 employees

Full-time

Posted 24 days ago


Job description

We are looking for an Applied AI Architect with strong hands-on experience in AI/ML architecture, development, and production deployment. The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems.

Must-Have Technical Skills
  • Strong hands-on experience in AI/ML development and production deployment.
  • Experience with Databricks, MLflow, Unity Catalog, Delta Lake, and model serving.
  • Experience with Azure AI Foundry and modern AI/ML platforms.
  • Strong knowledge of RAG and LLM application architecture.
  • Experience building multi-agent systems and workflows.
  • Experience with MCP/tool calling and frameworks such as LangGraph, Semantic Kernel, or OpenAI Agents SDK.
  • Strong Python development skills for production AI/ML applications.
  • Experience with CI/CD, MLOps, and AIOps.
  • Knowledge of LLM/RAG/agent evaluation, observability, tracing, and monitoring.
  • Experience with production debugging and performance optimization.
  • Ability to create reusable AI accelerators, templates, skills, and reference implementations.
Roles & Responsibilities
  • Define and implement AI/ML architecture and solutions.
  • Work closely with engineering and business teams to build and deploy AI models.
  • Design and develop LLM, RAG, and multi-agent solutions.
  • Establish best practices for AI evaluation, deployment, monitoring, and production support.
  • Improve and standardize applied AI delivery patterns.
  • Accelerate AI adoption through reusable components, templates, and reference architectures.
  • Provide technical leadership and guidance to AI/ML engineering teams.